Stigma towards mental disorders in Qatar: A qualitative study
Bibliographic record
Abstract
Background: Across the world, people with mental health disorders experience various levels of stigma. Service users can provide valuable insight into the nature and extent of this stigma. In Qatar, mental health stigma was not well studied previously. Methods: This study was part of mixed-methodology research. The research team conducted interviews in English or Arabic with outpatient mental health clinic attendees who participated in a quantitative survey in Qatar. For the qualitative part of the study, the interview guide was developed after the results were analyzed for the pilot phase of a national quantitative survey that engaged nurses, physicians, patients, and family members in discussions about mental health stigma. All interviews were recorded and transcribed for coding and thematic analysis. Arabic-language interviews were translated into English by a certified translation service. A framework was developed, which eventually included eight main themes and five sub-themes relating to perceptions of mental illness, stigma, and avoidance of stigma. Results: Seven people, all with previous mental health diagnoses, were included in the qualitative study. The participants described instances of stigma. Most of them did not disclose their mental health diagnoses to others. Stigma among the participants was often experienced by proxy. Stigma towards mental disorders in Qatar was believed to be caused by poor understanding of these diagnoses, media portrayals of persons with mental disorders, and perceptions arising from cultural/religious beliefs. Modifying lifestyles and concealing diagnosis helped the participants to avoid stigma within Qatar. Conclusions: All the participants believed that mental illness diagnoses carried social stigma. Most of them described efforts to avoid disclosing mental health diagnoses to others based on a fear of negative social consequences. These findings offer insight into the perceptions of service users in Qatar towards stigma and self-stigma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".